Researching market and consumer trends often involves analysis of many types and levels of data. For example, markets may be affected by various macro and micro economic trends, seasonal trends, social trends, corporate trends, etc. Each of these trends may, in turn, be affected by many other types of trends. While some trends may be observed in the analysis of market data, they may be complex and not easily applied to marketing decisions. It may be difficult to understand consumer patterns and trends without supplementing large amounts of diverse types of market data with extensive amounts of data mining, analysis, and assumptions.
One approach to obtaining market data is to have public and private entities indirectly obtain such data through interviews and/or other techniques. For example, a government employee may contact representative merchant locations to ask about sales and overall performance for a given timeframe (e.g., the past month). Investors may then obtain and analyze this indirect market information in making investment decisions (e.g., a decision on whether or not to invest in a new store location).
These and other techniques, however, may provide limited market information. For example, interviewed merchants or merchant locations may provide inaccurate information, and specific merchant information may not actually be representative of actual market conditions. Further, delays in obtaining these types of market data may be undesirable for investors and/or other stakeholders.